• International journal of advanced smart convergence
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• v.10 no.1
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• pp.97-104
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• 2021

Securities and investment services had the most data per company on the average, and used the most data. Investors are increasingly demanding to invest through their own analysis methods. Therefore, securities and investment companies provide stock data to investors through open API. The data received using the open API is in text format. Python is effective and convenient for requesting and receiving text data. We investigate there are 22 major securities and investment companies in Korea and only 6 companies. Only Daishin Securities Co. supports Python officially. We compare how to receive stock data through open API using Python, and Python programming features. The open APIs for the study are Daishin Securities Co. and eBest Investment & Securities Co. Comparing the two APIs for receiving the current stock data, we find the main two differences are the login method and the method of sending and receiving data. As for the login method, CYBOS plus has login information, but xingAPI does not have. As for the method of sending and receiving data, Cybos Plus sends and receives data by calling the request method, and the reply method. xingAPI sends and receives data in the form of an event. Therefore, the number of xingAPI codes is more than that of CYBOS plus. And we find that CYBOS plus executes a loop statement by lists and tuple, dictionary, and CYBOS plus supports the basic commands provided by Python.

• Journal of Korea Trade
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• v.23 no.7
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• pp.147-155
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• 2019

Purpose - As the U.S.-China trade war has become considerably worse, the Chinese government is considering applying non-tariff barriers to trade, especially local contents rule. The main purpose of this research is to check whether it is suitable for Korean investors to invest in the current Chinese capital market. Design/methodology - In order to check the stability of the recent Chinese capital market, we investigated the behavior of foreign equity investment (including Korean equity investment) in the Chinese capital market after China announced the Shanghai-Hong Kong Stock Connect (SH-HK Connect). In this paper, we researched whether international portfolio investment would or would not contribute to an increase the volatility of an emerging market's stock market (Chinese capital market) when foreign investors make investment decisions based on the objective of short-term gains by rushing into countries whose markets are booming and fleeing from countries whose markets are falling. Findings - The empirical results indicate that foreign investors show strong, negative feedback trading behavior with regard to the stock index of the Shanghai Stock Exchange (SSE), and when the performance of foreign investors in the Chinese stock market was fairly good. Also, we found evidence that the behavior of foreign investors significantly decreased volatility in SSE stock returns. Consequently, the SH-HK Connect brought on a win-win effect for both the Chinese capital market and foreign investors. Originality/value - It appeared that the Chinese capital market was very suitable for Korean investors after the China's declaration of the SH-HK Connect. However, the win-win effect was brought on by the Chinese government's aggressive capital control but the capital controls could possibly cause financial turmoil in the Chinese capital market. Therefore, Chinese reform in industrial structure and the financial sector should keep pace with suitable capital control policies.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• Korean Management Science Review
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• v.29 no.2
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• pp.53-64
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• 2012

This paper is about the investment strategy in stocks on Fundamental analysis. Financial data of stocks from January 2. 2001 through October 30. 2009 were utilized in order to suggest the investment strategies. Fundamental analysis was used in stocks-related strategy. The portfolios are composed of 3 criteria such as the buying criteria score, exchange cycle and selling conditions. The buying criteria score is determined assigned to each stock index according to the satisfaction condition of 15 parameters selected considering the grue's criteria. The stock buying alternatives has two options with buying stocks over 13 points and over 14 points of buying criteria score. The seven exchange cycles and three selling methods are considered. So total number of portfolios is 42($2{\times}7{\times}3=42$). The simulation has been executed about each 42 portfolios and we figured out with the simulation result that 83.33% of 35 portfolios are more profitable than average stock market profit(203.43%). The outcome of this research is summarized in two parts. First, it's the exchange strategy of portfolio. The result shows that value-oriented investment (long-term investment) strategy yields much higher than short-term investment strategies of stocks. Second, it's about the exchange cycle forming the portfolios. The result shows that the rate of return for the portfolio is the best when exchange cycle is 18 months.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.1-14
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• 2015

In this paper, we investigate the relationship between Internet search trends and stock market. Under the assumption that investors may use Internet search engine to obtain information for companies of their interests before taking actual investment actions, the relationship between the changes on Internet search volume and the fluctuation of trading volume as well as stock price of a company is analyzed with actual market data. A search trend investment strategy that reflects the changes on Internet search volume is applied to large enterprises' group and to small and medium enterprises' (SMEs) group, and the correlation between profit rate and trading volume is analyzed for each company group. Our search trend investment strategy has outperformed average stock market returns in both KOSPI and KOSDAQ markets during the seven-year study period (2007~2013). It is also shown that search trend investment strategy is more effective to SMEs than to large enterprises. The relationship between changes on Internet search volume and stock trading volume is stronger at SMEs than at large enterprises.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.

• KDI Journal of Economic Policy
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• v.40 no.2
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• pp.23-52
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• 2018

Given the limited availability of data in South Korea, this study proposes a method by which to estimate regional capital stock by modifying the benchmark year method (BYM) and applies it to estimate regional net capital stock by sector in transport infrastructure. First, it estimates time-varying sectoral depreciation rates using the sectoral net capital stock and the investment amount for each period. Second, it estimates the net capital stock of each period using the net capital stock in the base year and the investment in each period. Third, in order to ensure that the sum of net capital stocks by region is equal to the nationwide estimate, the national estimates are allocated to each region according to the proportion of the values derived from the previous stage. The proposed method can alleviate well-known problems associated with conventional BYMs, specifically the upward bias and arbitrary choice of the depreciation rate.

• KDI Journal of Economic Policy
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• v.24 no.2
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• pp.83-119
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• 2002

In this paper, we study the relationship between the U.S. daily stock returns and the corresponding Korean returns. More specifically, we examine whether the previously realized U.S. stock returns would help predict the current Korean returns. We find that for dose-to-close daily stock returns, the U.S. returns would help predict the Korean returns. However, for open-to-close stock returns, the U.S. intraday stock returns would not help predict the corresponding Korean returns. After distinguishing investors by their nationality and types, we then examine whether there is a relationship between investors' net purchase of Korean stocks and the previous days' U.S. stock returns. We find that the amount of international investors' net purchase of Korean stocks today would vary significantly with the previous days' U.S. stock returns. The Korean individual investors and the Korean investment trust companies, however, would follow the opposite investment pattern.

• Korean Management Science Review
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• v.26 no.2
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• pp.19-35
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• 2009

This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1005-1015
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• 2020

This paper aims to propose a Comprehensive Decision Support Model to evaluate retail companies' financial performance traded on the Vietnam Stock Exchange Market. The financial performance has been examined in terms of the valuations ratios, profitability ratios, growth rates, liquidity ratios, efficiency ratios, and leverage ratios. The data of twelve companies from the first quarter to the fourth quarter of 2019 and the first quarter of 2020 were employed. The weights of 18 chosen financial ratios are calculated by using the Standard Deviation method (SD). Grey Relational Analysis technique was applied to obtain the final ranking of each company in each quarter. The results showed that leverage ratios have the most significant impact on the retail companies' financial performance and gives some long-term investment recommendations for stakeholders and indicated that the Taseco Air Services Joint Stock Company (AST), Mobile World Investment Corporation (MWG), and Cam Ranh International Airport Services Joint Stock Company (CIA) are three of the top efficient companies. The three of the worst companies are Viglacera Corporation (VGC), Saigon General Service Corporation (SVC), and HocMon Trade Joint Stock Company (HTC). Furthermore, this study suggests that the GRA model could be implemented effectively to ranking companies of other industries in the future research.